A stochastic-dynamical model (SDM) for Indian Ocean Dipole (IOD)

Overview

In Stuecker et al. 2017, GRL and Zhao et al. 2019, GRL, we proposed a null hypothesis framework for the IOD. The dynamical evolution of IOD SST can be determined by seasonal modulated Indian Ocean feedbacks forced by ENSO and stochastic forcings. The IOD Mode Index (DMI) tendency can be written as

$$\frac{dT}{dt}=-\lambda\left(t\right)T\left(t\right)+\alpha\left(t\right)T_\text{ENSO}\left(t\right)+\sigma_0\xi\left(t\right)$$

where $T$ is the monthly DMI, $T_\text{ENSO}\left(t\right)$ the monthly Niño-3.4 index, $\lambda\left(t\right)$ the damping rate of $T$, $\alpha\left(t\right)$ the ENSO forcing strength, $\xi\left(t\right)$ the stochastic forcing, and $\sigma_0$ the magnitude of stochastic forcing.

Citation

The SDM for the IOD are described in the following papers, which should be referenced if you use SDM for the IOD in publications:

• Stuecker, M. F., A. Timmermann, F.-F. Jin, Y. Chikamoto, W. Zhang, A. T. Wittenberg, E. Widiasih, S. Zhao (2017), Revisiting ENSO/Indian Ocean Dipole phase relationships, Geophys. Res. Lett., 44(5), 2481–2492, https://doi.org/10.1002/2016GL072308
• Zhao, S., F.-F. Jin, M. F. Stuecker (2019) Improved Predictability of the Indian Ocean Dipole Using Seasonally Modulated ENSO Forcing Forecasts. Geophys. Res. Lett., 46(16):9980-9990, https://doi.org/10.1029/2019GL084196

We ask that you acknowledge us in your use of the SDM for the IOD in any documents or publications. Thank you!

Availability to the code

For those finding of interest in using the SDM for the IOD, please email me zhaos@hawaii.edu) to get the model code. We would appreciated if you can briefly introduce your plan about the use of this model.